唐山工业职业技术学院

Background Oral carcinoma is a prevalent malignancy with limited therapeutic options, highlighting the need to elucidate molecular mechanisms driving tumor progression. Aim This study explores the interplay between LKB1 and STAT3 signaling pathways in Oral carcinoma pathogenesis. Methods Two Oral carcinoma cell lines including HSC-3 and KB were used. Results We demonstrate that honokiol, an LKB1 activator, unexpectedly enhances the growth of oral carcinoma cells, while genetic knockdown of LKB1 further promotes cell proliferation, suggesting a context-dependent tumor-suppressive role for LKB1 in Oral carcinoma. Mechanistically, honokiol inhibits phosphorylation of STAT3 (p-STAT3), a key oncogenic driver, in oral carcinoma cells. Consistent with this, pharmacological inhibition of p-STAT3 using Stattic suppresses Oral carcinoma cell growth, whereas activation of STAT3 with Colivelin promotes proliferation, underscoring the critical role of STAT3 signaling in Oral carcinoma progression. Importantly, Colivelin rescues honokiol-mediated growth inhibition, indicating that honokiol exerts its antitumor effects, at least in part, through suppression of STAT3 activity. These findings reveal a novel crosstalk between LKB1 and STAT3 pathways in oral carcinoma and suggest that targeting STAT3 signaling may represent a promising therapeutic strategy for oral cancer. Conclusion This study provides new insights into the molecular mechanisms underlying oral carcinoma progression and identifies potential targets for therapeutic intervention.

Oxide metallurgy is a critical technique for enhancing the welding performance of hull steel in high-heat-input welding applications. Its fundamental principle involves controlling the formation of beneficial composite inclusions and ensuring their uniform distribution within the steel matrix to facilitate grain refinement. In this study, EH40 hull steel with a multi-element Mo-Nb-Al-Mg-Ti system was investigated. The production process required ladle refining and magnesium–titanium treatment. The atomic-scale adsorption mechanism of MnS on the MgAl 2 O 4 surface was examined through a combination of first-principles calculations and microscopic characterization. A 10 × 10 × 10 mm steel plate sample was prepared for scanning electron microscopy (SEM) analysis, while a transmission electron microscope (TEM) sample was extracted using an FEI Scios focused ion beam system. SEM and TEM observations revealed that the complex inclusions consisted of an MgAl 2 O 4 core with attached Ti 2 O 3 precipitates, while MnS encapsulated the outer surface. The adsorption interface between MgAl 2 O 4 and Ti 2 O 3 was identified, with some Mn atoms bonding to titanium oxide. A bulk model with space group Fd-3 m, a lattice parameter of 0.8075 nm, and 56 atoms was constructed using Findit software. The adsorption energy, structural configuration, and electronic interactions of S and Mn atoms on the MgAl 2 O 4 (100)-Mg surface were analyzed through a two-step computational approach, considering different initial positions and adsorption sequences. The results confirmed that the TO1 site was the most favorable adsorption site for MnS on the MgAl 2 O 4 (100)-Mg surface, with an adsorption energy of −9.2 eV. The MnS growth mechanism involved the initial adsorption of Mn atoms onto the MgAl 2 O 4 (100)-Mg surface, followed by vertical growth into a cross-quaternary ring crystal structure.

The adaptive neuro-fuzzy inference system (ANFIS) analysis is used in this paper to introduce a ground-breaking method for predicting compressive strength f^'_C of recycled aggregate concrete (RAC). Due to the complex interplay between various components, designing the right mixture proportions to obtain the desired f^'_C can be challenging. Algorithms for machine learning (ML) have shown much promise in successfully tackling this complexity. This research presents a semi-empirical method that seamlessly incorporates optimization techniques in the pursuit of improved prediction accuracy. Examining a dataset consisting of 441 observations, this study extensively investigates the properties of concrete. The research focuses on analyzing key input variables, including but not limited to the water-to-cement ratio, coarse aggregate to cement ratio, cement fineness, fine aggregate to total aggregate ratio, specific gravity of saturated surface-dry aggregates, and water absorption of aggregates. In addition, this study uses two meta-heuristic techniques, beluga whale optimisation (BWO) and electric charged particles optimisation (ECPO), to improve the models’ accuracy. The research produces three distinct models, ANEC, ANBW, and a single ANFIS model, and each offers insightful information for precise f^'_C . Based on the results, the ANBW model outperforms all others with a noteworthy R2 value of 0.993 and a remarkably low RMSE value of 1.299. These findings not only confirm the ANBW model’s precision and dependability but also show how well it can forecast f^'_C results. This method has much potential for accurate f^'_C forecasting in the construction sector.

This article first describes the embedded voice processing process and uses the two-door restriction method for endpoint detection. Next, the wavelet + MFCC algorithm is proposed. The Fourier transform will replace it with ripple. The disadvantage of the ripple is that the size of the Fourier transform window cannot move with frequency. On this basis, the overall goal of the system is proposed, the overall structure is constructed, and the functions of the system are divided. Android mobile phone data collection technology has been extensively researched, including logical search, temporary access to permissions, JTAG search and ISP search. The design and implementation of the logical search engine based on root authority, the physical search engine based on Qualcomm processor, and the data analysis system have been completed, and the evidence collection of e-commerce applications has been completed. Based on the digital forensics system, this article studies and designs an Android device digital forensics system suitable for China's national conditions and laws from the three perspectives of data collection, analysis and storage. At the same time, brainstorming methods must be used between corporate financial management and cost management personnel. Finally, through research, scientifically construct the framework of the financial cost management system, distinguish the various requirements of the construction system, classify the importance, urgency, and feasibility of the requirements, establish the basic requirements and extension requirements, set the demand function to complete the schedule and Perform as planned. Through the research of embedded voice and digital forensics system, this paper applies it to the research of financial cost management, thereby promoting the development of enterprise financial management.

This is an article in the field of mining engineering.Kaolinite and montmorillonite are the main clay minerals in coal slime,and clay minerals are the main factors affecting the sedimentation of coal slime.This paper takes clean coal,kaolinite and montmorillonite as the research objects.The influence of ultrasonic intensity,action time,and ultrasonic pulse interval on its sedimentation effect and floc diameter was investigated.The test results show that when the ultrasonic density is 0.4 W/cm3,when the ultrasonic action time is 2 min,the sedimentation speed of kaolinite and montmorillonite are improved.Further choosing the appropriate ultrasonic pulse interval can further improve the sedimentation effect,but ultrasonic treatment is not conducive to the clean coal settlement.Further,the clean coal,kaolinite and montmorillonite samples were mixed at a ratio of 2∶1∶1,and the ultrasonic pulse interval time was changed to perform ultrasonic treatment.The results showed that:for the mixed sample,it settled without ultrasonic treatment,the velocity is 2.67 cm/min.When the ultrasonic density is 0.2 W/cm3 and the ultrasonic pulse interval is 4 s,the settling velocity is increased to 5.41 cm/min.Image analysis and potential characterization show that the proper ultrasonic pulse interval time enables the drug to play more fully,and then the electric double layer is compressed to the greatest extent,and finally the particle agglomeration and the growth of flocs are the best.